Step 4: Configuring Subagent and A2A Parameters

Configuring Subagent Parameters

When a Subagent is added to the canvas, a dedicated parameter configuration panel appears. This panel allows you to define the subagent’s behavior, scope, and interactions within the workflow. It enables precise control over how input is handled, what the subagent is expected to do.

For example: You are an Invoice Processing Agent. Extract invoice number, vendor, amount, and date from incoming documents and flag discrepancies.

You can also specify how the input is passed to the agent, and how the agent’s response or extracted data is used in the next steps of the workflow.

The configuration interface is organised into three key tabs:

This structured approach to subagent configuration allows users to build precise, purpose-driven AI agents with role-specific instructions and tool integrations - without writing any code.

Mandatory Parameters

Use this tab to capture the fundamental attributes and prompt settings required to initialize the subagent.

Option Description
*Indicates mandatory field
Subagent Name * Enter a specific name for this subagent. If it is the primary agent, it will default to "New Subagent" but should be renamed to something meaningful that reflects its role within the workflow.
LLM/SLM

This section allows you to configure the Large Language Model (LLM) or Small Language Model (SLM) that your agent will use for generating or processing responses.

You can select an existing provider and profile, or create a new profile to define credentials and model configurations.

  • Use agent's LLM/SML: Select this to use the global or default LLM/SML settings configured for the parent agent or application.
  • Set a different LLM/SML: Select this to override the default settings and manually specify a different model provider and profile. This option activates the Provider and Profile fields.
Note: For more details, refer Configuring LLM/SLM Provider and Profile Settings, in Configuring Parameters page.

Prompt

This section is critical for guiding the LLM's behavior for this specific subagent.
Role*

Specify the subagent’s functional role or identity the AI agent should adopt for its specific tasks within the workflow. This guides how the agent interprets instructions.

Example: Customer Support Specialist, Financial Analyst.
Scope*

Define the subagent’s area of responsibility or task boundaries within the larger workflow.

Example: Analyze financial statements for Q3 2025.

Instructions

Use this tab to provide clear, detailed step-by-step instructions and rules that guide the AI agent's reasoning and execution. These instructions are specific to the subagent's role and scope.

  • Click the Add Instruction + button to define one or more step-by-step instructions.

  • Each instruction should be concise and directive to ensure the AI performs accurately and consistently.

Actions

In this tab you can define the external tools or functions that the subagent is allowed to invoke during execution. This enables the agent to interact with third-party systems or trigger downstream actions

Option Description

Tools: Add Tool
Click Add Tool, then choose the required tool from the Tool Category dropdown list.
Note: You can find detailed information about each Tool Category and its specific configuration options in the Tools Library page.

Configuring A2A gateway configurations

The A2A Node acts as an A2A Client within your workflow, enabling the agent to delegate tasks and consume specialized capabilities from another remote AI Agent. By leveraging the open Agent2Agent (A2A) Protocol, this node ensures secure, standardized communication and seamless collaboration between AI agents, regardless of their underlying platform or vendor. This capability is essential for creating robust, modular multi-agent systems.

When a A2A subagent is added to the canvas, a dedicated parameter configuration panel appears. This panel allows you to define the A2A subagent’s behavior, scope, and interactions within the workflow. It enables precise control over how input is handled, what the subagent is expected to do.

Option Description
*Indicates mandatory field
Name * A user-friendly unique ID assigned to the delegated agent. Example: ItineraryPlannerAgent
Base URL*

The base URL of the remote service. Your sub-agent uses this endpoint to automatically discover the capabilities listed on the remote agent's Agent Card.

Example: https://api.travel-ai.com.
Credential Type*

The type of security credential specified by the remote agent. This must be selected before supplying the credential.

Example: Bearer Token Crdential
Credential* The actual authentication value (for example, API key string, tok) required to access the remote agent. The format depends on the scheme defined in the Agent Card.
Note: Defining the Credential is mandatory for secure Agent-to-Agent communication, ensuring only authenticated, trusted interactions occur within enterprise environments.

How A2A Communication Works

The Sub-Agent communicates with a remote A2A Exposed AI Agent through a structured sequence involving discovery, authentication, and task execution. The process is as follows:

1. Discovery Using the Base URL

The Sub-Agent begins by accessing the remote agent’s Base URL to retrieve its Agent Card.

The Agent Card is a JSON manifest that provides essential metadata, including:

  • The agent’s name and description

  • Its available skills and capabilities

  • The service endpoint for task submission

  • The authentication method required (which determines the appropriate Credential configuration)

This discovery step enables the Sub-Agent to understand how to interact with the remote agent and what operations it can request.

2. Authentication Using Credentials

Based on the authentication method declared in the Agent Card, the Sub-Agent uses the configured Credential to securely authorize communication.

This ensures that only trusted, authenticated agents can send delegated tasks to the remote agent.

3. Task Communication

After successful authentication and capability discovery, the Sub-Agent sends a Task request—the core work unit in A2A communication.

Tasks are submitted via JSON-RPC over HTTP(S) to the remote agent’s service endpoint (typically derived from the Base URL).

This establishes a structured, secure communication channel for delegating and executing work.